Two-stage registration of substrcutures in magnetic resonance brain images

Authors:
S. Yousefi;N. Kehtarnavaz;K. Gopinath;R. Briggs
Affiliations:
Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX;Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX;Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX;Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 1
Cited 0

Automatic subcortical structure segmentation using probabilistic atlas

ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

Image registration is a key component in existing magnetic resonance image processing software packages. Because of nonlinear variability in brain substructures, the commonly used registration pipelines applied to the entire brain area may not lead to accurate registration for substructures. This paper presents a two-stage registration approach for a better alignment of brain substructures or regions-of-interest. In the first stage, an affine transformation function is applied to the entire brain area and in the second stage, a nonrigid or deformable transformation function is applied to the substructure of interest. To show the usefulness of this two-stage registration, images from the Brainweb database are examined using normalized mutual information is used to assess the degree of alignment. The comparison results indicate improvements over the commonly used registration approaches.